An effective clustering scheme for high-dimensional data

While the classical K -means algorithm has been widely used in many fields, it still has some defects. Therefore, this paper proposes a scheme to improve the clustering quality of K -means algorithm. The farthest initial center selection and the min–max rule are used to improve the random initializa...

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Bibliographic Details
Published in:	Multimedia tools and applications Vol. 83; no. 15; pp. 45001 - 45045
Main Authors:	He, Xuansen, He, Fan, Fan, Yueping, Jiang, Lingmin, Liu, Runzong, Maalla, Allam
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.05.2024 Springer Nature B.V
Subjects:	Algorithms Cluster analysis Clustering Computer Communication Networks Computer Science Data Structures and Information Theory Datasets Discriminant analysis Empirical analysis Multimedia Information Systems Normal distribution Special Purpose and Application-Based Systems Linear discriminant analysis Silhouette analysis Clustering validity function Initial center selection Empirical rule means algorithm
ISSN:	1573-7721, 1380-7501, 1573-7721
Online Access:	Get full text
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